Computational study of putative functional variants in human kisspeptin

Abstract Non-synonymous single nucleotide polymorphisms (nsSNPs) are a type of genetic mutations that result in amino acid substitution of the encoded proteins that may potentially affect its function and phenotype. An In Silico assay has been carried out by using bioinformatics prediction tools to identify nsSNPs which are responsible for important disorders in human kisspeptin (KISS1) gene. In this study, for the first time, KISS1 amino acid changes were discovered by tBlastn for EST database. A list of nsSNPs in human KISS1 gene from dbSNP, dbEST and UniProt databases were prepared. Computational analysis was performed using SIFT (Sorting Intolerant From Tolerant) and PolyPhen (Polymorphism Phenotyping) programs. Of the total 92 nsSNPs, 20 were found to be damaged by both servers. Six nsSNPs (P97L, G122R, W114C, R92C, R120H and N115K) are predicted with the highest damaging scores (SIFT = 0, PolyPhen = 1). These intolerant changes may suggest their functional significance in critical regions which may affect the function and stability of KISS1 protein. Identifying these nsSNPs among the thousands of them make an opportunity to screen only those predicted deleterious by programs.